Fixed-Fractional Position Sizing
Fixed-fractional position sizing risks a constant fraction of current account equity on every trade, so the rupee bet grows as the account grows and shrinks as it falls, producing geometric compounding and a self-limiting response to drawdowns.
Quick Answer
Fixed-fractional sizing risks a set fraction of current equity each trade, so units = (f × capital) ÷ (stop × point value), re-read before every trade. At 1% of Rs 5,00,000 the bet grows to Rs 7,000 once the account reaches Rs 7,00,000. It compounds and de-risks after losses, but results are path-dependent, so validate with Monte Carlo.
Definition: Fixed-Fractional Position Sizing
Fixed-Fractional Position Sizing is risking a constant fraction of current account equity on every trade, so the rupee bet grows as the account grows and shrinks as it falls, producing geometric compounding.
Key takeaways: Fixed-Fractional Position Sizing
- Fixed-fractional sizing risks a constant fraction of current capital, so bets compound with the account
- Units = (f × capital) ÷ (stop distance × point value), re-read before every trade
- It de-risks automatically after losses, giving a far lower risk of ruin than aggressive fixed sizing
- Percentage drawdown scales with the fraction f, which is the main lever you control
- Results are path dependent, so validate with Monte Carlo rather than one compounded curve
Fixed-Fractional Position Sizing at a glance
| Method | Risk a constant fraction f of current equity |
|---|---|
| Formula | units = (f × capital) ÷ (stop distance × point value) |
| Growth | Geometric, compounding |
| After losses | Rupee bet shrinks automatically (anti-martingale) |
| Risk of ruin | Far lower than equally aggressive fixed sizing |
| Main lever | Fraction f — drawdown scales with it |
| Blind spot | Path-dependent; one curve is one realisation |
Fixed-Fractional Position Sizing in simple words
Fixed-fractional sizing means you risk the same percentage of your current capital on each trade, for example 1 percent, rather than a fixed number of lots. When the account grows you bet more rupees; when it shrinks you bet less. This makes the account compound in good times and automatically pull back exposure after losses, which is why it is one of the most widely used sizing rules.
What Fixed-Fractional Position Sizing is for
Fixed-fractional sizing exists to make risk scale with capital rather than stay static, giving geometric growth while building in an automatic de-risking response to losing streaks so that no single run of losses is fatal.
Fixed-Fractional Position Sizing — professional explanation
The core mechanism and formula
Fixed-fractional sizing sets the quantity so that a fixed fraction f of current equity is at risk if the stop is hit. The number of units is the rupee risk budget divided by the per-unit risk: units = (f × capital) ÷ (stop distance × point value). Because capital is re-read before every trade, the bet compounds: a rising account raises the rupee bet, a falling account cuts it. This is the defining property that separates it from fixed sizing, where the quantity ignores the account balance entirely.
Why it compounds geometrically
When each trade risks the same percentage, gains and losses multiply rather than add. A sequence of returns r1, r2, r3 applied to capital produces a terminal wealth proportional to the product of (1 plus each return), not their sum. Over a long sample with a positive edge this geometric compounding dramatically outgrows the additive path of fixed sizing. The same mathematics, however, means the growth rate is governed by the geometric mean of outcomes, which is always less than the arithmetic mean, so volatility drags on compounded growth in a way fixed sizing hides.
The self-limiting response to drawdowns
Because the rupee bet is a fraction of shrinking equity, fixed-fractional sizing automatically reduces exposure during a losing streak. After a 20 percent drawdown the account is smaller, so the next 1 percent bet is 1 percent of a smaller number, cutting the absolute risk. This anti-martingale behaviour is the reason risk of ruin under fixed-fractional sizing is far lower than under an equally aggressive fixed scheme: you cannot reach zero by linear steps because each loss shrinks the next bet. The cost is a slower recovery, since you also bet less on the way back up.
Choosing the fraction and the drawdown trade-off
The fraction f directly controls the trade-off between growth and drawdown. Too small and the account barely moves; too large and normal variance produces punishing equity swings, because percentage drawdowns scale roughly with f. There is an optimal-growth fraction, given by the Kelly criterion, beyond which increasing f actually lowers long-run growth while still raising volatility. Practitioners almost always bet a fraction well below the Kelly optimum, often a half or a quarter of it, trading some growth for a much smoother ride and a wider margin against estimation error.
Backtesting implications and path dependence
A fixed-fractional backtest is path dependent: the same set of trades in a different order produces a different terminal wealth and a different maximum drawdown, because the bet size at each point depends on the running equity. This means a single compounded equity curve is only one realisation, and Monte Carlo reshuffling of the trade sequence is essential to understand the distribution of outcomes and the realistic drawdown range. It also means you must feed the sizing model the true per-trade risk, including realistic stop distances after slippage and costs, or the compounded figures will be optimistic.
Formula
units = (f × capital) ÷ (stop distance × point value)
units = number of shares, lots or contracts to trade (round down to a whole lot in F&O); f = fraction of capital risked per trade, e.g. 0.01 for 1 percent; capital = current account equity in rupees; stop distance = points between entry and stop-loss; point value = rupee change per one-point move for one unit (for a Nifty lot of 65 — revised from 75 by NSE effective 28 Oct 2025, circular NSE/FAOP/70616 — point value = Rs 65 per index point).
How Fixed-Fractional Position Sizing looks visually
Worked example: Fixed-Fractional Position Sizing
Illustrative example (Indian market)
On capital of Rs 5,00,000 you risk f = 1 percent per trade, so the risk budget is Rs 5,000. Your Bank Nifty setup (Bank Nifty lot 30, revised from 35 by NSE eff. 28 Oct 2025, circular NSE/FAOP/70616) has a stop 120 points away and a point value of Rs 30 per point per lot of 30 units, so per-lot risk is 120 × 30 = Rs 3,600. Units = 5,000 ÷ 3,600 = 1.39, which you round down to 1 lot. After a good run the account reaches Rs 7,00,000, so the same 1 percent is now Rs 7,000 and, with the same stop, you would size 7,000 ÷ 3,600 = 1.94, still rounded down to 1 lot. The risk budget compounded with the account and the fractional target rose from 1.39 to 1.94 lots, but because NSE lots are indivisible the position only steps up to 2 lots once equity clears the two-lot boundary at Rs 7,20,000, where the 1 percent budget of Rs 7,200 exactly funds 7,200 ÷ 3,600 = 2 lots. That is fixed-fractional sizing working as designed: the intended bet grows continuously with the account while the actual position increases in whole-lot jumps.
Because NSE lots are indivisible, the rounded-down unit count means a small account crosses sizing thresholds in jumps. On Rs 5,00,000 at 1 percent you might afford only 2 Nifty lots, and you will not reach 3 lots until equity and the risk budget grow enough to clear the whole-lot boundary, so the compounding is stair-stepped rather than smooth for retail F&O traders.
Fixed-fractional vs Fixed size
| Aspect | Fixed-fractional | Fixed size |
|---|---|---|
| Held constant | Fraction of capital risked | Quantity traded |
| Growth | Geometric, compounding | Additive, near-linear |
| After losses | Bet shrinks automatically | Fraction at risk rises |
| Risk of ruin | Much lower for equal aggression | Higher, linear path to zero |
| Path dependence | Strong; order of trades matters | Weaker; each trade independent |
Limitations of Fixed-Fractional Position Sizing
- Terminal wealth is path dependent, so one compounded curve is only a single realisation of many possible orders
- The geometric mean governs growth, so volatility drags on compounded returns more than fixed sizing reveals
- Recovery from drawdown is slow because the bet also shrinks on the way back up
- Lot indivisibility forces rounding, so a small F&O account jumps between sizes rather than scaling smoothly
- It relies on an accurate stop distance and per-trade risk; underestimating them makes the compounded curve optimistic
Why Fixed-Fractional Position Sizing matters in practice
- It converts a per-trade edge into geometric account growth while automatically de-risking after losses
- It makes drawdown depth a direct function of the chosen fraction, which is the main lever a trader controls
How professionals treat Fixed-Fractional Position Sizing
Institutional and professional systematic traders treat the risked fraction as the central risk dial and set it deliberately below the Kelly optimum, commonly at a half or quarter Kelly, to buy robustness against estimation error and fat tails. They validate the sizing with Monte Carlo reshuffling of the trade sequence to see the distribution of terminal wealth and drawdown rather than a single path, and they feed the formula post-cost, post-slippage stop distances so the compounded figures are honest. The fraction is often reduced further during regime uncertainty or after a strategy has underperformed its expected drawdown envelope.
Common misconceptions about Fixed-Fractional Position Sizing
Misconception: A bigger fraction always means more growth.
Reality: Beyond the Kelly-optimal fraction, increasing the bet lowers long-run growth while still raising volatility, because compounded growth follows the geometric mean. Over-betting can turn a positive edge into a shrinking account.
Common mistakes with Fixed-Fractional Position Sizing
- Betting at or above the Kelly-optimal fraction, which raises volatility while lowering long-run growth
- Reading capital once at the start instead of before each trade, which turns it back into fixed sizing
- Ignoring path dependence and trusting a single compounded curve instead of Monte Carlo reshuffling
- Forgetting to round down to whole lots, overstating the achievable size on a small F&O account
- Using an unrealistically tight stop in the formula, which inflates unit count and understates risk
- Confusing fraction of capital risked with fraction of capital deployed as notional exposure
Fixed-Fractional Position Sizing: frequently asked questions
What is the fixed-fractional sizing formula?
Units = (f × capital) ÷ (stop distance × point value), where f is the fraction risked such as 0.01, capital is current equity, stop distance is the points to your stop, and point value is the rupees per point for one unit. Round the result down to whole lots in F&O.
How is fixed-fractional different from fixed sizing?
Fixed sizing holds the quantity constant while risk drifts, whereas fixed-fractional holds the risked percentage constant so the rupee bet moves with the account. The first grows additively; the second compounds geometrically.
Why does fixed-fractional sizing compound?
Because each trade risks the same percentage, returns multiply rather than add. Terminal wealth is proportional to the product of one plus each return, so a positive edge grows the account geometrically over a long sample.
Why are fixed-fractional results path dependent?
Because the bet size at each trade depends on running equity, the same trades in a different order give a different terminal wealth and drawdown. A single compounded curve is only one realisation, which is why Monte Carlo reshuffling is important.
How does lot indivisibility affect fixed-fractional sizing?
In NSE F&O you must round down to whole lots, so a small account crosses size thresholds in jumps rather than scaling smoothly. The compounding is therefore stair-stepped for retail traders.
Can I convert a fixed-size backtest to fixed-fractional?
You must re-run the identical signals through the sizing formula rather than rescale the result, because the compounded path and drawdowns change once the bet size depends on running equity.
Voice search: how people ask about Fixed-Fractional Position Sizing
Natural-language questions people ask about Fixed-Fractional Position Sizing.
What is fixed-fractional position sizing in plain words?
It means risking the same percentage of your account on every trade, like 1 percent, so you bet more rupees when the account grows and less when it shrinks. That makes it compound in good times and pull back after losses.
How do I calculate fixed-fractional size?
Take the fraction times your capital to get your rupee risk, then divide by the stop distance times the point value. That gives the number of lots, which you round down in F&O.
Why does risking a fixed percentage protect me?
Because after a loss your account is smaller, so the same percentage is a smaller bet. You keep shrinking the bet as you lose, so it is very hard to go all the way to zero.
Sources & references
- Vince, R. (1992). The Mathematics of Money Management. John Wiley & Sons.
- Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill.
Published 11 July 2026. Educational content only — not investment advice. Markets and rules change; verify current conventions with SEBI, NSE/BSE and your broker.